Minimum Required Sample Size Research Articles

COVID-19 exposure during pregnancy and low birth weight in community development blocks, Purba Bardhaman: A retrospective cohort study.

COVID-19 exposure during pregnancy is hypothesized to affect the birth weight of the children. Community based findings on such hypothesis are scarce in West Bengal. This study was conducted with the objective to determine the relationship between low birth weight (LBW) and maternal exposure to COVID-19. In this retrospective cohort study, mothers of children, who were born between February 2020 and October 2021 and who were registered in the subcenters of Purba Barddhaman district, West Bengal, were selected as study population. Mothers who were diagnosed as COVID-19 positive during the antenatal period were considered as 'Pregnancy with COVID' and others were considered as 'Pregnancy without COVID'. The minimum required sample size using Fleiss formula were 119 and 476, respectively, whose were selected through multi-stage random sampling. A schedule was used to collect data through review of relevant records of antenatal registers of sub-centers of selected individuals. The association was checked through multivariate logistic regression model where P < 0.05 was considered statistically significant. Incidence of LBW in COVID pregnancy, Non-COVID Pregnancy group were 30.3% and 18.7%, respectively. COVID positivity during pregnancy shows relative risk of 1.62 and attributable risk of 38.28% for LBW baby as pregnancy outcome. Multivariate analysis reveals that LBW babies are significantly associated with COVID status during pregnancy (AOR 2.18, 1.3-3.63) after adjusting for anemia in pregnancy, incomplete antenatal visits, mothers age ≥30 years, parity and periods of gestation. The study concludes that COVID positivity during pregnancy significantly increases the risk of LBW as pregnancy outcome.

Calculating the Sample Size in Quantitative Studies

The determination of the required sample size is always an important step during the planning of the quality of research for a quantitative study. The researchers need to have sound prerequisite knowledge of the inferential statistics concept for determining a minimum sample size requirement and its estimation because an insufficient sample size may not be able to answer the research questions and a large sample is wastage of resources, may add to the complexity, and take more time for the study. Both situations are ethically unacceptable for the researchers. Therefore, this study provides researchers with appropriate sample size determination methods for quantitative study. The Google Scholar, PubMed, and Library Genesis were used to find out the required information for the review of this paper. This study presents the sample size calculation formula in a simplified manner with relevant examples so that researchers may effectively use them in their research.

The Prevalence of Tourette Syndrome and Other Tic Disorders in Saudi Arabia

Background: Tic disorders (TD), including Tourette syndrome, are considered as one of the prevalent neurological conditions across the world which affects pediatric population. Tourette syndrome (TS), also called Gilles de la Tourette syndrome or Tourette disorder, a clinical subtype of TD with the most severe and persistent symptoms, is a complex multifaceted neurodevelopmental disorder characterized by multiple motor and at least one phonic tic starting before the age of 18 and lasting for at least 1 year.&#x0D; Objectives: Our study is designed to assess the prevalence of Tourette syndrome and other tic disorders among Saudi population and examine the sociodemographic factors including age, sex, education, and birthplace.&#x0D; Methods: A cross-sectional survey study conducted in Saudi population. An online questionnaire utilized to collect information from the population via various social media applications. The required minimum sample size is determined to be 384 participants. For statistical analyzation, the Statistical Package of Social Science Software (SPSS) program, version 20 (IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM Corp.) was used.&#x0D; Results: The study sample consisted of 2793 participants, 73% of them were females and 27% were males. 43.6% aged between 20- 30 years old and 33.4% aged less than 20 years old. 9.7% of participants suffer from Tourette syndrome while 5.7% of participants have a child who suffer from Tourette syndrome. Regarding co-morbid diseases, 23.7% suffer from anxiety disorder, 16.7% have sleeping disorder, 16.2% have depression, 10.8% eating disorder and 9.9% have obsessive-compulsive disorder. As for children with Tourette syndrome, 20.3% suffer from anxiety disorder, 19.5% have sleeping disorder, 18% have attention deficit hyperactivity disorder, 13.5% eating disorder and 7.9% have obsessive-compulsive disorder.&#x0D; Conclusion: Prevalence of TS among adults and children is higher than reported in previous figures. TS is associated with psychological and neurological diseases especially among children. TS should no longer be considered merely a motor disorder and, most importantly, that TS is no longer a unitary condition, as it was previously thought. Clinical assessment of children with chronic tic disorders warrants examination of other problems such as ADHD, disruptive behavior and anxiety.

Highway Safety Manual Calibration: Estimating the Minimum Required Sample Size

Crash frequency has been identified by many experts as one of the most important safety measures, and the Highway Safety Manual (HSM) encompasses the most commonly accepted predictive models for predicting the crash frequency on specific road segments and intersections. The HSM recommends that the models be calibrated using data from a jurisdiction where the models will be applied. One of the most common start-up issues with the calibration process is how to estimate the required sample size to achieve a specific level of precision, which can be a function of the variance of the calibration factor. The published research has indicated great variance in sample size requirements, and some of the sample size requirements are so large that they may deter state departments of transportation (DOT) from conducting calibration studies. In this study, an equation is derived to estimate the sample size based on the coefficient of variation of the calibration factor and the coefficient of variation of the observed crashes. Using this equation, a framework is proposed for state and local agencies to estimate the required sample size for calibration based on their desired level of precision. Using two recent calibration studies, South Carolina and North Carolina, it is shown that the proposed framework leads to more accurate estimates of sample size compared with current HSM recommendations. Whereas the minimum sample size requirement published in the HSM is based on the summation of the observed crashes, this paper demonstrates that the summation of the observed crashes may result in calibration factors that are less likely to be equally precise and the coefficient of the variation of the observed crashes can be considered instead.

Using the Barthel Index and modified Rankin Scale as Outcome Measures for Stroke Rehabilitation Trials; A Comparison of Minimum Sample Size Requirements

ObjectivesUnderpowered trials risk inaccurate results. Recruitment to stroke rehabilitation randomised controlled trials (RCTs) is often a challenge. Statistical simulations offer an important opportunity to explore the adequacy of sample sizes in the context of specific outcome measures. We aimed to examine and compare the adequacy of stroke rehabilitation RCT sample sizes using the Barthel Index (BI) or modified Rankin Scale (mRS) as primary outcomes. MethodsWe conducted computer simulations using typical experimental event rates (EER) and control event rates (CER) based on individual participant data (IPD) from stroke rehabilitation RCTs. Event rates are the proportion of participants who experienced clinically relevant improvements in the RCT experimental and control groups. We examined minimum sample size requirements and estimated the number of participants required to achieve a number needed to treat within clinically acceptable boundaries for the BI and mRS. ResultsWe secured 2350 IPD (18 RCTs). For a 90% chance of statistical accuracy on the BI a rehabilitation RCT would require 273 participants per randomised group. Accurate interpretation of effect sizes would require 1000s of participants per group. Simulations for the mRS were not possible as a clinically relevant improvement was not detected when using this outcome measure. ConclusionsStroke rehabilitation RCTs with large sample sizes are required for accurate interpretation of effect sizes based on the BI. The mRS lacked sensitivity to detect change and thus may be unsuitable as a primary outcome in stroke rehabilitation trials.

Developing clinical prediction models when adhering to minimum sample size recommendations: The importance of quantifying bootstrap variability in tuning parameters and predictive performance.

Recent minimum sample size formula (Riley et al.) for developing clinical prediction models help ensure that development datasets are of sufficient size to minimise overfitting. While these criteria are known to avoid excessive overfitting on average, the extent of variability in overfitting at recommended sample sizes is unknown. We investigated this through a simulation study and empirical example to develop logistic regression clinical prediction models using unpenalised maximum likelihood estimation, and various post-estimation shrinkage or penalisation methods. While the mean calibration slope was close to the ideal value of one for all methods, penalisation further reduced the level of overfitting, on average, compared to unpenalised methods. This came at the cost of higher variability in predictive performance for penalisation methods in external data. We recommend that penalisation methods are used in data that meet, or surpass, minimum sample size requirements to further mitigate overfitting, and that the variability in predictive performance and any tuning parameters should always be examined as part of the model development process, since this provides additional information over average (optimism-adjusted) performance alone. Lower variability would give reassurance that the developed clinical prediction model will perform well in new individuals from the same population as was used for model development.

Gender Analysis of Fish Production in Gambela Region, Ethiopia

Women’s access to and control over productive resources is highly constrained in most of the developing world. These constraints are usually overlooked. Gender analysis is very crucial to unpack the existing constraints and see the gap that affects technology transfer among men and women. The Objective of this study is to conduct gender analysis of capture fishery in selected woredas in Gambela region. The study was conducted in four purposively selected woredas of Anua Zone, Gambela region. Sample selection was done on household bases. Out of the 520 fisher households in the woredas, 10% of them are taken based on the minimum standard sample size requirements for social sciences. Among these, 190 were female (FHHHs) while 330 were male headed households (MHHHs). The determination of sample size is based on PPS to the size of the overall population engaged in fisheries. As a result, 19 FHHHs and 33MHHHs were included in the research. Quantitative data was collected using structured questionnaire from 52 households. In addition, a focus group discussion was made to elicit more information on gender roles and relationships. The output of the study indicated that, men in MHHHs are entirely responsible for the fishing activity. In addition, women &amp; youth in MHHHs have a significant role in maintaining the daily harvest of fish. Women in FHHHs are traditionally represented for collecting, processing, cooking and selling the catch. Though decision on selling the catch is mainly carried out by men, women were also found to have a say. Despite women’s involvement in value adding processes of capture fishery, a significant gap was observed between men and women headed households in accessing extension services. Thus, there is a significant difference in volume of fish harvested per fish type per day which was 10.5 and 7.5 kilograms per day for Male headed household and female headed household respectively. Daily fish catch of women headed household should be increased by offering improved fishing equipments. Keywords: Gender analysis, MHHHs, FHHHs, Capture fishery, Gambella region DOI: 10.7176/JNSR/12-19-03 Publication date: October 31 st 2021

Behavioral intention to use cryptocurrency in Malaysia: an empirical study

PurposeThe purpose of this study is to empirically examine the factors influencing consumer behavioral intention (BI) to use cryptocurrency as a medium of transaction. Constructs from the unified theory of acceptance and use of technology model and an added variable, perceived risk (PR), are examined to predictBI. Age and gender as moderators are retained in this model.Design/methodology/approachAn online survey was used to gather the respondents’ responses on a five-point Likert scale. G * Power was used to calculate the required minimum sample size. A non-probability sampling technique was used to gather data from the 290 respondents based in Malaysia. The final data set was analyzed using the statistical package for the social sciences and SmartPLS software using structural equation modeling.FindingsThe results show that three of the five proposed factors (performance expectancy, effort expectancy and facilitating condition) are significant predictors ofBIto adopt cryptocurrency as a medium of transaction. Interestingly,PRis not a significant predictor even though prior research studies showed otherwise. Likewise, the relationship betweenBIand social influence became significant only when age is added as a moderator.Practical implicationsMalaysians are still wary of cryptocurrency, even though global tech firms such as Amazon and Microsoft are already accepting Bitcoin as a payment method. This study aims to provide relevant authorities and businesses (i.e. central bank, retail merchants and cryptocurrency exchangers) insights toward understanding the factors consumers focus on if they were to use cryptocurrency as a medium of transaction.Originality/valueMost cryptocurrency research are done in developed countries (i.e. USA, UK and EU) perspective. This research addresses the lack of quantitative literature on significant factors influencingBIto use cryptocurrency in developing country context while taking aPR, age and gender into consideration.

Precise determination of 6Li/7Li isotopic ratio with NaLiBO2+ ion using total evaporation and ion integration by Thermal Ionization Mass Spectrometry(TIMS)

Total Evaporation and Ion Integration technique (TE & II) was used for determination of the 6Li/7Li isotope ratio with the NaLiBO2+ (m/z 71–73) and Na2BO2+ (m/z 88, 89) molecular ions emitted from the sodium lithium borate compound on the single filament assembly. Since the ion intensities are simultaneously collected by the multi-collector assembly and integrated till the sample is completely consumed, the measured ion intensity ratio 72I/73I is less affected by fractionation and hence closer to the true value. The fractionation profile for lithium isotopes showed concurrence with the Rayleigh's distillation law since the measured instantaneous ratio of 72I/73I at ∼63% sample consumption was equal to the integrated value at 100% sample consumption. The minimum sample size requirement for molecular ion method decreased to 50 ng of lithium for the TE method of data acquisition compared to 1–2 μg of lithium required for conventional method of limited scans. The relative standard deviation of 6Li/7Li ratio determined from the analyses of six samples of 500 ng each of the two natural Li2CO3 samples namely L-SVEC and high purity Spec-pure lithium was about 0.05% (1σ). Refractory materials Li2TiO3 and LiAlO2 were also successfully analysed by the developed TE method with reduced sample size. The TE method enhanced the benefits of the molecular ion method by further decreasing the effect of fractionation as well as sample size requirement for accurate determination of 6Li/7Li ratio. The method could clearly distinguish between the two natural lithium samples, L-SVEC lithium and Spec pure lithium having a difference of 0.5% in their 6Li/7Li ratio.

Minimum training sample size requirements for achieving high prediction accuracy with the BN model: A case study regarding seismic liquefaction

The complexity of a Bayesian network (BN) model and the number of training samples used have significant impacts on the prediction accuracy of the model regarding seismic liquefaction. The required training sample size for ensuring that a BN model has high generalization ability is a critical issue in parameter learning. To address this issue, this study analyses the relationship between the predictive performance of the BN model and the complexity of the model, training sample size, and average discrete intervals. Taking seismic liquefaction prediction as an example, 4536 statistical experiments are designed to investigate the training and testing performances of 21 different BN models under the conditions of nine different training sample size ratios (5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80% of all data) and testing samples using 20% of all data. The results reveal that the learning performance of a BN is not sensitive to the training sample size but is related to the complexity of the model. The larger the sample size is, the stronger the generalization ability of the model. The minimum training sample requirements are related to the maximum in-degrees and the average discrete intervals, not the numbers of nodes and edges and the maximum out-degree of the BN structure. In addition, a modified structural entropy can characterize the complexity of a BN structure better than the existing structural entropy, but it has a worse relationship with the minimum training sample requirements than that of the maximum in-degree. To quickly determine the minimum training sample size requirements of a BN model with a predictive accuracy of 80%, a fitting function that considers the effects of the maximum in-degree and the average discrete intervals is presented, and its effectiveness is validated by two examples.

Sample size calculation for Mann-Whitney U test with five methods

&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Precise sample size estimation plays a vital role in the planning of a study specifically for medical treatment expenses that are expensive and studies that are of high risk.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Among a variety of sample size calculation methods for the nonparametric Mann-Whitney U test, five potential methods are selected for evaluation in this article. The evaluation of method performance is based on the results obtained from high precision Monte Carlo simulations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The sample size deviations (from the simulation ones) are performance indicators. The sum of the squared deviations over all scenarios is used as the criterion for ranking the five methods. For power comparisons, the percentage errors (relative to the simulated powers) are used. The effect size and target power both have large impacts on the minimum required sample sizes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Based on the ranking criterion, Shieh's method has the best performance. Noether's method always overestimates the minimum required sample sizes but not too severe.&lt;/p&gt;

Abusive supervision and knowledge hiding in service organizations: exploring the boundary conditions

PurposeDespite burgeoning interest in knowledge hiding (KH), there are still significant gaps in the understanding of the boundary conditions under which KH is more or less likely to occur. To address this research gap, the researchers examined abusive supervision as an interpersonal antecedent of KH. In addition, this paper aims to investigate the moderating roles of negative reciprocity beliefs (NRB) and moral disengagement (MD) in the relationship between abusive supervision and KH.Design/methodology/approachTwo-wave data using a non-experimental face-to-face method was collected from 257 service employees in Pakistan, which supported the hypothesized model. Considering minimum sample size requirements (i.e. n = 208) in partial least squares structural equation modeling, the researchers analyzed a two-stage approach to test the measurement model and the structural model.FindingsThe study found that abusive supervision was positively related to evasive hiding and playing dumb but not associated with rationalized hiding. Further, the results confirm the moderating roles of NRB and MD. The positive relationships between abusive supervision and evasive hiding and playing dumb are intensified at high levels of NRB and MD.Originality/valueGiven the complicated nature of KH, this is one of the few efforts that outstretch the boundary conditions of KH.

Systematic review and quality evaluation of published human ingestion-time trials of blood pressure-lowering medications and their combinations

ABSTRACT The pharmacokinetics (PK) – absorption, distribution, metabolism, and elimination – and pharmacodynamics (PD) of hypertension medications can be significantly affected by circadian rhythms. As a consequence, the time when blood pressure (BP) lowering medications are ingested, with reference to the staging of all involved circadian rhythms modulating PK and PD, can affect their duration of action, magnitude of effect on features of the 24 h BP profile, and safety. We conducted a systematic and comprehensive review of published prospective human trials that investigated individual hypertension medications of all classes and their combinations for ingestion-time differences in BP-lowering, safety, patient adherence, and markers of hypertension-associated target organ pathology of the kidney and heart. The systematic review yielded 155 trials published between 1976 and 2020 – totaling 23,972 hypertensive individuals – that evaluated 37 different single and 14 dual-combination therapies. The vast (83.9%) majority of them reported clinically and statistically significant benefits – including enhanced reduction of asleep BP mean without induced sleep-time hypotension, reduced prevalence of the higher cardiovascular risk non-dipper 24 h BP profile, decreased incidence of adverse effects, improved kidney function, and reduced cardiac pathology – when hypertension medications are ingested at-bedtime/evening rather than upon-waking/morning. Nonetheless, the findings and conclusions of some past conducted trials are inconsistent, often due to disparities and deficiencies of the investigative protocols. Accordingly, we developed a quality assessment method based upon the eight items identified as crucial according to the recently published guidelines of the International Society for Chronobiology and the American Association for Medical Chronobiology and Chronotherapeutics for the design and conduct of human clinical trials on ingestion-time differences of hypertension medications. Among the most frequent deficiencies are: absence or miscalculation of minimum required sample size (83.2%), incorrect choice of primary BP endpoint (53.6%), and inappropriate arbitrary and unrepresentative clock hours chosen for tested treatment times (53.6%). The inability of the very small proportion (16.1%) of trials to verify the advantages of the at-bedtime/evening treatment strategy is likely explained by deficiencies of their study design and conduct. Nonetheless, regardless of the quality score of the 155 trials retrieved by our systematic review, it is most noteworthy that no single published prospective randomized trial reported significantly enhanced BP-lowering, safety, compliance, or other benefits of the unjustified by medical evidence, yet still most recommended, upon-waking/morning hypertension treatment-time scheme.

A Monte Carlo Simulation Study on the Influence of Unequal Group Sizes on Parameter Estimation in Multilevel Confirmatory Factor Analysis

ABSTRACT Unequal group sizes (imbalance) and small sample sizes are common in multilevel confirmatory factor analyses (ML-CFA). This simulation study examined the influence of imbalance combined with small sample sizes on both levels on estimation performance in ML-CFA. Imbalance did not influence estimation performance given the minimum sample size requirements. Greater sample sizes on one level compensated for smaller sample sizes on the respective other level. Additionally, the degree of intraclass correlation () interacted with sample sizes. Based on the results of the simulation study, recommendations for practical applications are delineated. For instance, at least 100 Level-2 units with an average cluster size of four or 150 Level-2 units with an average cluster size of two are recommended given an of .30 or above.

Recruiting for research on sensitive topics in schools: an experience with Vaxcards, a collectable vaccine card game

Undertaking recruitment for research in schools is an effective way to recruit young people for research participation but it is not without its challenges. Gaining access and coordinating many levels of different organisations and stakeholders whose cooperation and approval are crucial all add time and sometimes logistical challenges for the research team. In addition, recruiting around sensitive research topics can elicit additional barriers to successful research.The research team aimed to conduct a pragmatic cluster randomised controlled trial involving schools in a local government region in Victoria, Australia, to assess the effect of a vaccination-based educational card game called “Vaxcards” on vaccine consent returns. Schools were contacted via phone and email to determine which staff member would best be a contact point for a face-to-face meeting to discuss the methods and purpose of the study. Email follow-ups were scheduled to follow up non-responsive schools and consent forms. The minimum required sample size was 13.Of 31 eligible schools, 13 were recruited. The research team encountered several unanticipated challenges before achieving the recruitment target. The most common reasons for non-participation were being too busy with other commitments, concerns regarding the topic of vaccination being too sensitive, and concerns that key stakeholders in the school would not approve of the research topic of vaccination. One school required a review by a private research ethics board that rejected the study. Significant hesitancy and misinformation about vaccine science was observed that affected engagement with a small number of schools.This paper highlights the challenges of recruiting schools in the context of public anxieties about vaccines and has several important learning lessons for successful recruitment about sensitive topics. This includes navigating approval processes for research in schools, the importance of local champions, dealing with misinformation and the importance of strong relationships and organisational trust.Trial registrationAustralian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12618001753246. Prospectively registered on 25 October 2018 8:24:21 AM

Perceived Social Norms as Determinants of Adherence to Public Health Measures Related to COVID-19 in Bali, Indonesia.

Introduction: Before the widespread availability of an effective COVID-19 vaccine, it is crucial to control the rate of transmission by ensuring adherence to behavioral modifications, such as wearing masks, physical distancing, and washing hands, all of which can be implemented as public health measures. Focusing on the conditions in Bali, this study explored the level of compliance to public health measures targeted at COVID-19 and identified the determinants of compliance via the values, rules, and knowledge approach.Materials and Methods: This cross-sectional study conducted an online survey using the Google Form application from June 29 to July 5, 2020. The minimum required sample size was 664. Inclusion criteria were set as follows: 18 years of age or older and residing in Bali during the data collection period. Adherence was measured based on nine protocol indicators that were rated using a four-point Likert scale. A multiple linear regression analysis was then conducted to determine the associated factors of adherence to public health measures.Results: Of the 954 survey respondents, data from 743 were included for analysis. The average level of adherence to public health measures was 32.59 (range of 20–36). The linear regression analysis showed that perceived health benefits from public health measures, being female, and having COVID-19 test histories were significantly associated with adherence to public health measures.Conclusions: For public health measures targeted at COVID-19, adherence was strongly associated with perceived social norms, in which individuals played social community roles by adapting to standardized public health measures. It is thus imperative for governments to support and monitor public health measures during the COVID-19 pandemic.

Sample Size Requirements for Simple and Complex Mediation Models.

Mediation models have been widely used in many disciplines to better understand the underlying processes between independent and dependent variables. Despite their popularity and importance, the appropriate sample sizes for estimating those models are not well known. Although several approaches (such as Monte Carlo methods) exist, applied researchers tend to use insufficient sample sizes to estimate their models of interest, which might result in unstable and inaccurate estimation of the model parameters including mediation effects. In the present study, sample size requirements were investigated for four frequently used mediation models: one simple mediation model and three complex mediation models. For each model, path and structural equation modeling approaches were examined, and partial and complete mediation conditions were considered. Both the percentile bootstrap method and the multivariate delta method were compared for testing mediation effects. A series of Monte Carlo simulations was conducted under various simulation conditions, including those concerning the level of effect sizes, the number of indicators, the magnitude of factor loadings, and the proportion of missing data. The results not only present practical and general guidelines for substantive researchers to determine minimum required sample sizes but also improve understanding of which factors are related to sample size requirements in mediation models.

Working From Home Facilities Model During Pandemic Situation

Since WHO declare COVID-19 as a pandemic, it has changed the way of our life today. Mostly, all countries in the world implementing lockdown or movement control to stop the spreading. In Malaysia, the government announced a Movement Control Order (MCO) which requires the closure of all businesses except those providing essential services and items. This affects most business operations and companies have to switch to Working From Home (WFH). This paper aim to propose WFH Facilities Model during a pandemic (COVID-19). The scope of this study pertains to Malaysian citizens. The main methods used in this research were a deductive approach that suit to cross-sectional research. This research employs a simple random sampling technique to achieve the required minimum sample size. Therefore, to gather data, a questionnaire survey technique was selected.Meanwhile, using the SmartPLS3, structural equation modeling (SEM) technique was used to test the research hypotheses. A total of 500 questionnaires was circulated via a web-based self-administered questionnaire using the Google Forms survey. Out of 500 questionnaires distributed, only 363 sets were replied to and completed with a high response rate of up to 73%. The findings of the study show that from six research hypotheses, only two hypotheses are supported which are Work-Family Related (WF) and Modern Technology (MT).Hence, this study recommends that it is important for any organisation that wants to implement WFH to pay an attention to both attributes.

A Step-by-Step Process on Sample Size Determination for Medical Research.

Determination of a minimum sample size required for a study is a major consideration which all researchers are confronted with at the early stage of developing a research protocol. This is because the researcher will need to have a sound prerequisite knowledge of inferential statistics in order to enable him/her to acquire a thorough understanding of the overall concept of a minimum sample size requirement and its estimation. Besides type I error and power of the study, some estimates for effect sizes will also need to be determined in the process to calculate or estimate the sample size. The appropriateness in calculating or estimating the sample size will enable the researchers to better plan their study especially pertaining to recruitment of subjects. To facilitate a researcher in estimating the appropriate sample size for their study, this article provides some recommendations for researchers on how to determine the appropriate sample size for their studies. In addition, several issues related to sample size determination were also discussed.

A study on complications of proximal femoral nails in management of intertrochanteric fracture

Most intertrochanteric fractures occur in patients above 50 yrs who have additional systemic problems and functional disability. So the goal to treatment is early mobilization and return to pre operative functional state. Current treatment approach is possible anatomical reduction and rigid fixation. Considering the mean harris hip score as 93 and assuming the standard deviation as 4, with 5% relative precision and 95% confidence level, the minimum required sample size is 23. However 70 patients were selected for our study. Among the early complications that were being evaluated, 3 patients had superficial infections which were treated by a course of antibiotics. 1 patient had a stage 1 pressure sore which was managed with daily dressing. The wound healed well. 1 patient had backing out of the lag screw at immediate post op period. This was probably because the lag screw was inserted into the fracture site. However at 3 months and 6 months of follow up there was no further backing out of the screw and the fracture united well.